Fast and Enhanced Algorithm for Exemplar Based Image Inpainting (Paper# 132)

Inpainting: The art of restoring lost/selected parts of an image based on the background information in a visually plausible way.

Use exemplar-based approach, i.e., fill the missing region in patches.

The order of filling decides the final output. Order based on priority of patches. Calculate priority based

on confidence and data value of patch. Find the patch with maximum priority (Ψp)

Find a patch (Ψq) from background that has minimum mean squared error (MSE) with Ψp.

For patches with same MSE, minimize the variance of Ψq w.r.t. mean of Ψp.

Search in a fixed window around Ψp to save time.

The proposed algorithm shows improvements in quality of the obtained result as well as time taken.

It is capable of propagating both linear structures and two dimensional textures into the target region.

It is capable of filling small scratches as well as removing larger objects from the image.

Authors: Anupam Agrawal, Pulkit Goyal, Sapan Diwakar(anupam@iiita.ac.in, pulkit@daad-alumni.de, sapan@daad-

alumni.de)

Fast and Enhanced Algorithm for Exemplar Based Image Inpainting (Paper# 132)

Serial No.

Image Size (in pixels) Percentage area to be removed Time taken (in milliseconds)

   Data Sets   Criminisi Our Algorithm

1. 124032 0.81 11,223 2,2832. 60492 2.80 11,546 4,0423. 120000 5.00 53,971 27,3194. 60492 14.62 61,286 52,3785. 225000 60.79 1,357,690 1,337,850

a. Input Image b. Our output c. Output from *Criminisi’s

algorithm

qualitytime taken

* A. Criminisi, P. Perez, and K. Toyama, “Region Filling and object Removal by Exemplar- Based Image Inpainting,” IEEE Transactions on Image Processing, 13(9), 1200-1212, 2004.